ArticleGenes2023
DraculR: A Web-Based Application for In Silico Haemolysis Detection in High-Throughput microRNA Sequencing Data.
Article in Genes, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed, 2 citations in OpenAlex.
- Systems biology integration of miR-mRNA profiles identifies steroid refractoriness mechanisms and biomarker candidates in ulcerative colitis.Biochemistry and biophysics reports · 2026Article
- Regulation and Interaction Among SOCS1 and SOCS3 by MicroRNAs in Multiple Sclerosis: A Review andThe Yale journal of biology and medicine · 2026Review
- Hemolysis Analysis and Hemolysis-related MicroRNA Candidates for Serum/Plasma Samples.Current molecular medicine · 2026Review
- Optimized RT-qPCR and a novel normalization method for validating circulating miRNA biomarkers in ageing-related diseases.Scientific reports · 2023Article
- Article
Corrections and comments
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Authors and funding
9 authors at 4 institutions in 1 country.
Funding
Abstract
The search for novel microRNA (miRNA) biomarkers in plasma is hampered by haemolysis, the lysis and subsequent release of red blood cell contents, including miRNAs, into surrounding fluid. The biomarker potential of miRNAs comes in part from their multicompartment origin and the long-lived nature of miRNA transcripts in plasma, giving researchers a functional window for tissues that are otherwise difficult or disadvantageous to sample. The inclusion of red-blood-cell-derived miRNA transcripts in downstream analysis introduces a source of error that is difficult to identify posthoc and may lead to spurious results. Where access to a physical specimen is not possible, our tool will provide an in silico approach to haemolysis prediction. We present DraculR, an interactive Shiny/R application that enables a user to upload miRNA expression data from a short-read sequencing of human plasma as a raw read counts table and interactively calculate a metric that indicates the degree of haemolysis contamination. The code, DraculR web tool and its tutorial are freely available as detailed herein.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.